Ranging is a process whereby a distance from a detector to an object of interest may be determined. Conventional ranging systems may serve one or more functions, including proximity sensing, remote sensing and/or three-dimensional (3D) imaging. These systems typically include an interrogation source (e.g., a light source) for illuminating the object of interest, and an image sensor array (e.g., a complementary metal oxide semiconductor (CMOS) image sensor) for registering a return signal from the interaction of the interrogation source and the object. Conventional light interrogation systems may capture images using a sequential frame-based image sensor and apply image processing and pattern recognition algorithms to the captured images. The algorithms are typically based on knowledge of the projected broadcast patterns (e.g. structured light) or phase correlated beam sweeps of the interrogation source. Typical image sensors require integration of many photons (e.g. 1000 or more photons) on each pixel in order to establish an optical signal of adequate signal-to-noise ratio (SNR), due to the limited sensitivity of each respective pixel. The SNR requirements of the conventional image sensor in turn create demands on the power of the light source (e.g., the interrogation beam which may be, for example, in the visible wavelength range and/or infrared (IR) wavelength range). Stated differently, the interrogation beam must be able to provide an adequate number of photons for detection, in order to extract meaningful information regarding the scanned environment (or object).
An image sensor having increased sensitivity (e.g., one including avalanche photodiodes) enables signal detection with fewer incident photons from the interrogation source, but also becomes more sensitive to background noise. When the range to an object of interest is large, the photons from the interrogation source have a large time-of-flight (TOF). For a system based on reflected (or backscattered) illumination from the object of interest, radiometric dissipation of the interrogation source (by 1/R4, where R=the range, due to the out-and-back path) requires that the interrogation source power be large in order to provide an adequate SNR over the large distances possible for detection. In such scenarios the signal from the “scene” may be overwhelmed by the background, (e.g., large radiation of a bright sunny day) which causes activation of the photodiodes in the image sensor prior to receipt of the interrogation signal returning from the object of interest. Traditionally, TOF ranging issues, especially power consumed (which typically scales with the distance to the interrogated object(s)), along with the size of other system components, limits the use of small form factor devices, e.g., handheld devices and/or wearables, for applications such as virtual and/or augmented reality. Conventional TOF-based systems are too power hungry and slow (regarding latency, and frame rate) to be practical for use in mobile phones, wearables, and other mobile applications.
In conventional systems, the whole image sensor array is sampled (all pixels) in order to develop a grayscale image. Achieving a high frame rate at low power with that scheme is not possible, when using high-definition (many pixels, e.g., 1280×720) image sensor—the data stream is too large. Further, image sensors having high resolution typically use a memory-inspired array address and readout architecture, which severely limits the temporal information available, this temporal information being related to the arrival time of photons to the sensor. Massive amounts of pixel data must be sorted to find the events of interest in the conventional image sensor, a process that can be very power-inefficient. Further, considering the great speed of light (approximately 0.3 meters per nanosecond), even a system capable of achieving fine timing resolution, e.g., 0.5 nanoseconds, would be limited in spatial resolution to 0.15 meters, which may be too unresolved for many applications.